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Regression Analysis

Regression analysis

You are given the following results from computations pertaining to a simple linear regression application. Y=5,723.0+145x n= 25 Sb1=10.80 a) based on the statistics supplied, can you conclude that there is a significant linear relationship between x and y? test at a significant level of 0.05 b) interpret the slope coef

Multiple Regression

A publishing company in New York is attempting to develop a model that can use to help predict sales for textbooks it is considering for future publication. The marketing department has collected data on several variables from a random sample of 15 books. These data are given in the attached excel file. Answer these questions

Simple Linear Regression

Interpreting Summary Output for Simple Linear Regression (Round all calculations to 4 places.) Using the second attached BALDOR data and Excel output, complete the following: 1. What is the value of the correlation coefficient? 2. What is the value of the coefficient of determination? 3. What is

Multiple linear regression analysis with Minitab

In this problem, a multiple linear regression analysis is done with the software Minitab and the results of the analysis are interpreted. Using the Minitab output, the following questions are answered. a) Report the estimated regression equation and the value of R-square. b) Construct a 95% confidence interval for the slope

Logistic regression

Multiple choice/ short answer See attached revisedq1.doc Word document for the multiple choice questions. Appears part of the information needed to answer was missing from the original posting. The information is now included in the revised document.

Forecasting Using Excel; Seasonality??

Using some historical data for the past 40 periods (see attachment) I need to make a forecast for the next 12 periods (periods 41 thru 52) using whatever is the best/most accurate of the simple forecasting techniques we have covered so far in our 2nd year class. These include: 1)Simple Moving Average 2)Weighted Moving Averag

Use Mean Absolute Deviation and Excel to forecast

Given a set of historical data (see attachment) I need to make a forecast for 26 periods using whatever is the best/most accurate of the simple forecasting techniques we have covered so far in our 2nd year class. These include: 1)Simple Moving Average 2)Weighted Moving Average 3)Exponential Smoothing 4)Linear Regre

Regression for forecasting

Using SPSS, MiniTab, or Excel and the data provided in the attached Excel spreadsheet see if sales (sales12x) is is influenced by the number of mailings (mail12x)and contacts( contacts)? Explain any other correlations you may discover. forcasting: For all of the customers that have had no sales (zero) in the (sales12x

Regression

Please see the attached file for full problem description. --- A popular, nationwide standardized test taken by high-school juniors and seniors may or may not measure academic potential, but we can nonetheless examine the relationship between scores on this test and performance in college. We have chosen a random sample of

Bivariate Data explained in this solution

Please see the attached file for full problem description. --- Bivariate data obtained for the paired variables and are shown below, in the table labelled "Sample data." These data are plotted in the scatter plot in Figure 1, which also displays the least-squares regression line for the data. The equation for this line is.

Log regression 2

This problem analyzes the asc.xls data set. The purpose of this problem is to predict which customers will respond to a particular catalog and how much they will spend. The variable targdols gives the amount that each customer spent in response to a particular mailing. The variables recency, totfreq, and totfreq give RFM for th

Log Regression

The marketing manager for a large nationally franchised lawn service company would like to study the characteristics that differentiate homeowners who do and do not have a lawn service. A random sample of 30 homeowners located in a suburban area near a large city was selected. Use the lawn.xls dataset in SPSS, Minitab or Excel.

1) Compute the expected number of months until canceling and LTV for retention rates of 80%, 85%, 90%, 95%, 97%, and 99%. Plot LTV against retention rate. 2) Construct box plots or histograms of the two variables separately.

Question 1) Consider a direct marketing company where customers become members, pay periodical fees, and cancel membership at some time, e.g., a CD club. Assume the annual discount rate is 8%. 1. Suppose that the expected monthly cash flow from customers is $15. Compute the expected number of months until canceling and LTV for

Regression analysis - describing relationships algebraically

Data from 60 cities has been collected to investigate how human mortality relates to different socioeconomic factors. The variables are: Mortality (age adjusted mortality) Education (median education) PopDensity (Population density) %Non-white (Percentage of non-whites) %WC (Percentage of white collar workers) Populatio

Important information about Bivariate Data

Please label your answers in bold and away from any calculations. Bivariate data obtained for the paired variables and are shown below, in the table labelled "Sample data." These data are plotted in the scatter plot in Figure 1, which also displays the least-squares regression line for the data. The equation for this line is

Computations

The least-squares regression line for these data has a slope of approximately 0.18. Answer the following. Carry your intermediate computations to at least four decimal places, and round your answers as specified below. (see attachment for full questions)

Time series data

Horace Mann, principal of Jones Public School, has decided to construct a time series model to obtain a 2- and a 3-period moving average to forecast student enrollments for next term. Which statement is true concerning the accuracy of each forecast that Horace will obtain? (which one) a. The 2-period forecast will be more accura

Seasonal Forescasting in Excel....

For this assignment, our teacher gave us data for 144 periods and asks us... "use the best forecasting technique for forecast 12 periods into the future. State all relevant assumptions, and briefly describe the technique(s) you used." Now, I'm assuming this would be a seasonal forecast, but I'm not sure what technique to

Demand forecast in Excel....seasonality

Generico has been manufacturing videotapes since 1982. The 3-hour VHS format is by far the largest component of their product mix. Historical demand for these items since 1992 is listed below <data attached>. Don Wirtz, general managing partner of Generico is concerned about the state of the current market for VHS format ta

Coefficient of regression

A survey shows the following relationship between advertisement and sales # of Ads Sales(000) 11 4 12 2 13 6 14 10 15 8 a) Compute the coefficient of regression for this survey b) What is the value of point of intercept?

Develop a simple linear regression analysis between Finley Heaters' sales and national housing starts. What percentage of variation in Finley Heaters' sales is explained by national housing starts? Would you recommend that Finley Heaters management use the forecast from Part a to plan facility expansion?

6. Finley Heaters Inc. is a mid-sized manufacturer of residential water heaters. Sales have grown during the last several years, and the company's production capacity needs to be increased. The company's management wonders if 'national housing starts' might be a good indicator of the company's sales: "

Time Series: seasonality, trend-seasonal model, seasonal indexes

Question 1 (30 pts.): The Excel file attendance.xls contains the daily attendance data at a theme park for a period of four weeks in summer. The park manager wants to use these data to make forecasts for the following summer week. a) Make a time-series plot of the data. Is there a trend? Is there seasonality in the data? Wha

Regression

A). Create a scatter plot (using excel) of the data. b). Find the equation of the linear regression line. c). Plot the regression line on the same plot as the data. d). How well do you think the line fits the data? e). Use the regression equation to predict the number of officers hired for each city. f). Calculate

Linear regression

A linear regression between Y and X produced the following equation for the least squares line: = -4.13 + 2.1x Which of the following statements concerning this relationship is true? a.For every one-unit increase in X, Y increases 4.13 units. b.For every one-unit increase in X, Y decreases 2.1 units. c.For ever